no code implementations • 25 Mar 2024 • Zerui Wang, Yan Liu, Abishek Arumugam Thiruselvi, Abdelwahab Hamou-Lhadj
In this study, we propose the early adoption of Explainable AI (XAI) with a focus on three properties: Quality of explanation, the explanation summaries should be consistent across multiple XAI methods; Architectural Compatibility, for effective integration in XAI, the architecture styles of both the XAI methods and the models to be explained must be compatible with the framework; Configurable operations, XAI explanations are operable, akin to machine learning operations.
1 code implementation • 12 Mar 2024 • Qinghao Hu, Zhisheng Ye, Zerui Wang, Guoteng Wang, Meng Zhang, Qiaoling Chen, Peng Sun, Dahua Lin, Xiaolin Wang, Yingwei Luo, Yonggang Wen, Tianwei Zhang
Large Language Models (LLMs) have presented impressive performance across several transformative tasks.
no code implementations • 22 Jan 2024 • Zerui Wang, Yan Liu
In addition to evaluating efficiency in terms of balanced accuracy and computing costs, adversarial attacks are potential threats to the robustness and explainability of AI models.
no code implementations • 2 Sep 2023 • Jiaqi Liu, Yonghao Long, Kai Chen, Cheuk Hei Leung, Zerui Wang, Qi Dou
However, this task is very challenging due to the small sizes of surgical instrument tips, and significant variance of surgical scenes across different procedures.